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08/17/2023
MindMap: Knowledge Graph Prompting Sparks Graph of Thoughts in Large Language Models
LLMs usually exhibit limitations in their ability to incorporate new kno...
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07/27/2023
Matching Patients to Clinical Trials with Large Language Models
Clinical trials are vital in advancing drug development and evidence-bas...
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06/06/2023
PyTrial: A Comprehensive Platform for Artificial Intelligence for Drug Development
Drug development is a complex process that aims to test the efficacy and...
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05/20/2023
AnyPredict: Foundation Model for Tabular Prediction
Foundation models are pre-trained on massive data to perform well across...
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05/19/2023
AutoTrial: Prompting Language Models for Clinical Trial Design
Clinical trials are critical for drug development. Constructing the appr...
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04/30/2023
DualHSIC: HSIC-Bottleneck and Alignment for Continual Learning
Rehearsal-based approaches are a mainstay of continual learning (CL). Th...
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04/07/2023
SPOT: Sequential Predictive Modeling of Clinical Trial Outcome with Meta-Learning
Clinical trials are essential to drug development but time-consuming, co...
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01/30/2023
Robust Meta Learning for Image based tasks
A machine learning model that generalizes well should obtain low errors ...
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01/26/2023
Invariant Meta Learning for Out-of-Distribution Generalization
Modern deep learning techniques have illustrated their excellent capabil...
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10/18/2022
MedCLIP: Contrastive Learning from Unpaired Medical Images and Text
Existing vision-text contrastive learning like CLIP aims to match the pa...
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10/09/2022
Pruning Adversarially Robust Neural Networks without Adversarial Examples
Adversarial pruning compresses models while preserving robustness. Curre...
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09/16/2022
Artificial Intelligence for In Silico Clinical Trials: A Review
A clinical trial is an essential step in drug development, which is ofte...
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06/29/2022
Trial2Vec: Zero-Shot Clinical Trial Document Similarity Search using Self-Supervision
Clinical trials are essential for drug development but are extremely exp...
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05/19/2022
TransTab: Learning Transferable Tabular Transformers Across Tables
Tabular data (or tables) are the most widely used data format in machine...
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01/12/2022
Deep Learning on Multimodal Sensor Data at the Wireless Edge for Vehicular Network
Beam selection for millimeter-wave links in a vehicular scenario is a ch...
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10/02/2021
SurvTRACE: Transformers for Survival Analysis with Competing Events
In medicine, survival analysis studies the time duration to events of in...
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09/29/2021
PAC-Bayes Information Bottleneck
Information bottleneck (IB) depicts a trade-off between the accuracy and...
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06/13/2021
Deep Bayesian Unsupervised Lifelong Learning
Lifelong Learning (LL) refers to the ability to continually learn and so...
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06/04/2021
Revisiting Hilbert-Schmidt Information Bottleneck for Adversarial Robustness
We investigate the HSIC (Hilbert-Schmidt independence criterion) bottlen...
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02/27/2021
Lifelong Learning based Disease Diagnosis on Clinical Notes
Current deep learning based disease diagnosis systems usually fall short...
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12/13/2020
Open-World Class Discovery with Kernel Networks
We study an Open-World Class Discovery problem in which, given labeled t...
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12/13/2020
Learn-Prune-Share for Lifelong Learning
In lifelong learning, we wish to maintain and update a model (e.g., a ne...
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09/17/2020
Finding Influential Instances for Distantly Supervised Relation Extraction
Distant supervision has been demonstrated to be highly beneficial to enh...
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09/06/2020
Online Disease Self-diagnosis with Inductive Heterogeneous Graph Convolutional Networks
We propose a Healthcare Graph Convolutional Network (HealGCN) to offer d...
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09/06/2020
Information Theoretic Counterfactual Learning from Missing-Not-At-Random Feedback
Counterfactual learning for dealing with missing-not-at-random data (MNA...
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01/25/2020
On the Fairness of Randomized Trials for Recommendation With Heterogeneous Demographics and Beyond
Observed events in recommendation are consequence of the decisions made ...
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12/03/2019
Less Is Better: Unweighted Data Subsampling via Influence Function
In the time of Big Data, training complex models on large-scale data set...
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06/07/2019
